Decoding early stress signaling waves in living plants using nanosensor multiplexing

Increased exposure to environmental stresses due to climate change have adversely affected plant growth and productivity. Upon stress, plants activate a signaling cascade, involving multiple molecules like H2O2, and plant hormones such as salicylic acid (SA) leading to resistance or stress adaptation. However, the temporal ordering and composition of the resulting cascade remains largely unknown. In this study we developed a nanosensor for SA and multiplexed it with H2O2 nanosensor for simultaneous monitoring of stress-induced H2O2 and SA signals when Brassica rapa subsp. Chinensis (Pak choi) plants were subjected to distinct stress treatments, namely light, heat, pathogen stress and mechanical wounding. Nanosensors reported distinct dynamics and temporal wave characteristics of H2O2 and SA generation for each stress. Based on these temporal insights, we have formulated a biochemical kinetic model that suggests the early H2O2 waveform encodes information specific to each stress type. These results demonstrate that sensor multiplexing can reveal stress signaling mechanisms in plants, aiding in developing climate-resilient crops and pre-symptomatic stress diagnoses.


Selectivity screening of SA aptamer wrapped SWNT (S5) with plant analytes
Upon screening with the same list of plant hormone analytes as shown in Figure 1d, we found S5 to be relatively inert to all plant hormones with the exception of IAA, which had a moderate quenching response of 18% (Supplementary Figure 2c).We posit that the lack of SA binding of the aptamer could be due to the disruption of aptamer conformation in the process of ultra-sonication during SWNT suspension, hence reducing its binding affinity.Interestingly, we discovered that S5 exhibits increasing binding affinity to SA, upon lowering of the excitation laser wavelength from 750 to 600 nm (Supplementary Figure 2d), resulting in an enlarged SWNT fluorescence quenching response.At t = 50 min, the fluorescence quenching measured after addition of 100 µM of SA, using a 600-nm excitation laser wavelength reached 80%.However, excitation lasers with lowered wavelengths overlap with the chlorophyll autofluorescence in plants, giving rise to high background fluorescence captured by the nIR camera.Hence, excitation lasers with longer wavelength at 785 nm and 830 nm are typically more compatible for experimental studies with living plant samples.In contrast, from the 2D excitation-emission map of S3 before and after introduction of SA (Supplementary Figure 3ab), similar magnitude of fluorescence quenching is observed for all SWNT chiralities across all excitation laser wavelengths from 500 to 800 nm.Hence, we find S3 to be the more suitable plant nanobionic sensor for SA.

Surface coverage of polymer wrapped SWNTs (S1-S4)
SWNT nIR fluorescence is known to quench in the presence of riboflavin for a variety of corona phases 1 .The magnitude of nIR fluorescence quenching upon addition of riboflavin is also correlated with the surface coverage of the particular corona phase, with smaller magnitude of fluorescence quenching indicative of a more tightly packed corona 2 .S1 and S2 have Pz and Pm co-monomers with para-linkages forming co-polymers that are highly rigid and rod-like while S3 and S4 have meta-linkages conferring more flexibility in the polymer structure 3 (Supplementary Figure 4a).When the riboflavin molecular probe was added, S1 and S2 have a smaller nIR fluorescence quenching magnitudes of 7.0% and 12.8% respectively compared to S3 and S4 with nIR fluorescence quenching magnitudes of 26.0% and 21.9% respectively (Supplementary Figure 4b).This is likely because S1 and S2 are capable of strong inter-chain π-π interactions that enable them to pack closer together on the SWNT surface, leaving less accessible surface area for analyte adsorption on the SWNT surface (Supplementary Figure 4c).As a result, they have relatively inert corona phases.Comparatively, S3 and S4 have enhanced conformational freedom that leaves larger surface area on the SWNT surface available for analyte adsorption.From the CoPhMoRe screening results, it is evident that both S3 and S4 could bind with different plant hormone analytes, resulting in fluorescence intensity modulations.Out of the two, the Pz co-monomer in S3 promoted better selectivity for SA, compared to Pm in S4, which had non-specific binding with a number of plant hormones.

Detailed method for SA concentration calculation using nanosensor calibration curve
The detailed method for SA concentration calculation is explained using the pipecolic acid experiment as an example.Firstly, the average fluorescence intensity is integrated over the entire sensor spot area harbouring many cells as shown in the brightfield image of the leaf (Supplementary Figure 8a).After sensor infiltration, the initial fluorescence intensity ( 0 ) represents the total basal SA levels present in the cells within the spot area prior to stress (t = 0 h), as illustrated by the false-color sensor intensity maps of the imaged leaf area (Supplementary Figure 8b).Representative false-color intensity maps are also shown for the same imaged leaf areas at t = 2 h, 4 h and 6 h post treatment with pipecolic acid.By integrating the intensity maps obtained over the 6 h time period, we can obtain fluorescence intensity time curves of the imaged leaf areas.The sensor fluorescence intensity changes ( −  0 ) in the same population of cells are calculated using  0 as normalization.The normalized intensity time curves (Supplementary Figure 8c) will have an initial intensity of "1".We then focus on detecting the normalized fluorescence intensity deviation post stress, which is indicative of overall amount of SA produced post stress within the sensor spot area.By taking an intensity ratio between the SA sensor and reference sensor which is non-responsive to SA over time (Supplementary Figure 8d), we further account for other sensor fluctuations unrelated to SA signaling in planta post stress.The normalized intensity ratios are then averaged across independent biological replicates.Using ImageJ software, SA concentration map images (Supplementary Figure 8e) can be converted from the respective false-color intensity maps by applying the SA sensor calibration curve at Figure 1g of , where A = 0.40558 and KD = 31.421μM.The normalized intensity ratio time curves can also be converted to SA concentration time curves with the same sensor calibration equation (Supplementary Figure 8f).This method allows us to precisely calculate the change in SA over the 6 h period post pipecolic acid treatment within the population of cells in the imaged area in planta and has been used consistently to calculate SA concentrations in all time course experiments reported in this paper.

H2O2 Waveform and SA Model
We propose the following general chemical mechanism to describe the stress-dependent H2O2 and SA signatures observed in Figure 7a-d All other species are initialized at zero.Equations S7-S14 were numerically simulated in MATLAB using the adaptive stiff ODE solver ode15s.Because the exact time of stress perception is unclear, especially for stresses applied over longer times, the model was fitted to data while allowing for a time shift  0 to approximately match the experimental H2O2 waveform peak location.Note that both model-generated H2O2 and SA were shifted by the same  0 , so the relative onsets of H2O2 and SA in the model were unchanged.

Confocal imaging to elucidate nanosensor movement post infiltration
In Lew, T.T.S. et al, Nature Plants 6 (2020), 404-415, it was observed that the ROS and reference sensors do not mix when infiltrated regions are separated by midvein 4 .To further confirm this, we evaluated the movement of sensors post infiltration by confocal imaging.The H2O2 nanosensor was tagged with Cy3 florescent dye and then the sensors were infiltrated into three distinct areas of the leaf that are partitioned by dominant veins of the pak choi leaf in the following manner.The Cy3tagged H2O2 sensor and SA sensor were individually infiltrated in two spots and then the two sensors were mixed and infiltrated into the third spot (Supplementary Figure 10).The intracellular localization pattern of both the sensors overlaps.We focused on the chloroplast localization of both sensors as it is easy to decipher by confocal.After 5hrs post infiltration, confocal scanning of the three infiltrated spots was performed.The region infiltrated with SA sensor showed no fluorescence from the Cy3-tagged H2O2 and conversely the area infiltrated with Cy3-tagged H2O2 showed no fluorescence from the SA sensor.The region where both the sensors were mixed and infiltrated, fluorescence from both the sensors could be observed.The above experiment indicate that the infiltrated sensors do not migrate out of their infiltrated regions.

Supplementary Figure 4 :
membrane.Mobile phase: 0.2% DMSO in DI water.Flow rate: 10 mL/min.S3 fluorescence was measured before and after addition of 100 μM SA (t = 0 h), periodically extracted from dialysis tube and measured at t = 1, 3, 5 and 7 h of dialysis.(a) PM3 geometry-optimized polymer backbone of S1 to S4 (3 repeat units) indicating enhanced conformational freedom of S3 and S4 polymers with meta-linkages compared to S1 and S2 polymers with para-linkages, possibly conferring improved selectivity for specific analyte binding.Nitrogen: blue; Carbon: dark grey; Hydrogen: light grey; (b) SWNT nIR fluorescence response of S1 -S4 to 10 μM riboflavin, indicative of differing SWNT surface coverage.Bar graph show the mean values with error bars representing standard deviations from independent experiments (n = 3).Dots represent each data point; (c) Schematic of S1-S4 polymer-wrapped SWNTs (grey) with either meta (S3-S4) or para (S1-S2) linkages within the polymer backbone (purple) while cationic side-chains (red) extend out into the solution matrix. :